constant x.xxxx

Inputs

  • 1
  • 2
  • 3
  • 4
  • 5

Outputs

  • constant x.xxxx

Neuron type

Best algorithm has been found - locked

Patterns

Pattern Input Output
1.
1: 1
2: 2
3: 3
4: 4
5: 5
constant x.xxxx: 1.2345
2.
1: 9
2: 8
3: 7
4: 6
5: 5
constant x.xxxx: 9.8765
3.
1: 5
2: 4
3: 3
4: 2
5: 1
constant x.xxxx: 5.4321

Applicable neurons

  • Connect - two inputs
  • constant x.xxx
  • -1
  • a < b
  • abc
  • Width of persons
  • character j

Algorithm

Test

Code made by AI:
/**
 * Connect - two inputs: 
 *
 * @param x1 Variable A
 * @param x2 Variable B
 * @return {Array}
 */
function neuron520(x1, x2)
{
return [x1.toString()+x2.toString()];
}

/**
 * Connect - two inputs: 
 *
 * @param x1 Variable A
 * @param x2 Variable B
 * @return {Array}
 */
function neuron520(x1, x2)
{
return [x1.toString()+x2.toString()];
}

/**
 * character .: 
 *
 * @return {Array}
 */
function neuron510()
{
return['.'];
}

/**
 * Connect - two inputs: 
 *
 * @param x1 Variable A
 * @param x2 Variable B
 * @return {Array}
 */
function neuron520(x1, x2)
{
return [x1.toString()+x2.toString()];
}

/**
 * constant x.x: Connect two numbers to number with a decimal point
 * 
 * @param x1 Number before the decimal point
 * @param x2 Number after the decimal point
 * @return {Array}
 */
function neuron539(x1, x2)
{
  var outputs = [];
  outputs[0] = x1;
  outputs[1] = x2;

  arr = neuron510();
  outputs[2] = arr[0];

  arr = neuron520(outputs[0], outputs[2]);
  outputs[3] = arr[0];

  arr = neuron520(outputs[3], outputs[1]);
  outputs[4] = arr[0];

  return[outputs[4]];
}


/**
 * constant x.xx: 
 * 
 * @param x1 1
 * @param x2 2
 * @param x3 3
 * @return {Array}
 */
function neuron711(x1, x2, x3)
{
  var outputs = [];
  outputs[0] = x1;
  outputs[1] = x2;
  outputs[2] = x3;

  arr = neuron520(outputs[1], outputs[2]);
  outputs[3] = arr[0];

  arr = neuron539(outputs[0], outputs[3]);
  outputs[4] = arr[0];

  return[outputs[4]];
}


/**
 * constant x.xxx: 
 * 
 * @param x1 1
 * @param x2 2
 * @param x3 3
 * @param x4 4
 * @return {Array}
 */
function neuron712(x1, x2, x3, x4)
{
  var outputs = [];
  outputs[0] = x1;
  outputs[1] = x2;
  outputs[2] = x3;
  outputs[3] = x4;

  arr = neuron520(outputs[2], outputs[3]);
  outputs[4] = arr[0];

  arr = neuron711(outputs[0], outputs[1], outputs[4]);
  outputs[5] = arr[0];

  return[outputs[5]];
}


/**
 * Connect - two inputs: 
 *
 * @param x1 Variable A
 * @param x2 Variable B
 * @return {Array}
 */
function neuron520(x1, x2)
{
return [x1.toString()+x2.toString()];
}

/**
 * constant x.xxxx: 
 * 
 * @param x1 1
 * @param x2 2
 * @param x3 3
 * @param x4 4
 * @param x5 5
 * @return {Array}
 */
function neuron713(x1, x2, x3, x4, x5)
{
  var outputs = [];
  outputs[0] = x1;
  outputs[1] = x2;
  outputs[2] = x3;
  outputs[3] = x4;
  outputs[4] = x5;

  arr = neuron712(outputs[0], outputs[1], outputs[2], outputs[3]);
  outputs[5] = arr[0];

  arr = neuron520(outputs[5], outputs[4]);
  outputs[6] = arr[0];

  return[outputs[6]];
}


Code made by AI:

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